These results demonstrate for the first time the feasibility of engaging seniors in a large-scale deployment of in-home activity assessment technology and the successful collection of these activity metrics. We plan to use this platform to determine if continuous unobtrusive monitoring may detect incident cognitive decline.

Background Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison to cognitively intact volunteers. Methods Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer usage (number of days with use, mean daily usage and coefficient of variation of use) measured by remotely monitoring computer session start and end times. Results Over 230,000 computer sessions from 113 computer users (mean age, 85; 38 with MCI) were acquired during a mean of 36 months. In mixed effects models there was no difference in computer usage at baseline between MCI and intact participants controlling for age, sex, education, race and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (p=0.01), mean daily usage (~1% greater decrease/month; p=0.009) and an increase in day-to-day use variability (p=0.002). Conclusions Computer use change can be unobtrusively monitored and indicate individuals with MCI. With 79% of those 55–64 years old now online, this may be an ecologically valid and efficient approach to track subtle clinically meaningful change with aging.

The Microsoft Kinect camera is becoming increasingly popular in many areas aside from entertainment, including human activity monitoring and rehabilitation. Many people, however, fail to consider the reliability and accuracy of the Kinect human pose estimation when they depend on it as a measuring system. In this paper we compare the Kinect pose estimation (skeletonization) with more established techniques for pose estimation from motion capture data, examining the accuracy of joint localization and robustness of pose estimation with respect to the orientation and occlusions. We have evaluated six physical exercises aimed at coaching of elderly population. Experimental results present pose estimation accuracy rates and corresponding error bounds for the Kinect system.

Physical performance measures predict health and function in older populations. Walking speed in particular has consistently predicted morbidity and mortality. However, single brief walking measures may not reflect a person’s typical ability. Using a system that unobtrusively and continuously measures walking activity in a person’s home we examined walking speed metrics and their relation to function. In 76 persons living independently (mean age, 86) we measured every instance of walking past a line of passive infra-red motion sensors placed strategically in their home during a four-week period surrounding their annual clinical evaluation. Walking speeds and the variance in these measures were calculated and compared to conventional measures of gait, motor function and cognition. Median number of walks per day was 18 ± 15. Overall mean walking speed was 61 ± 17 cm/sec. Characteristic fast walking speed was 96 cm/sec. Men walked as frequently and fast as women. Those using a walking aid walked significantly slower and with greater variability. Morning speeds were significantly faster than afternoon/evening speeds. In-home walking speeds were significantly associated with several neuropsychological tests as well as tests of motor performance. Unobtrusive home walking assessments are ecologically valid measures of walking function. They provide previously unattainable metrics (periodicity, variability, range of minimum and maximum speeds) of everyday motor function.

Gait velocity has been shown to quantitatively estimate risk of future hospitalization, has been shown to be a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a "sensor line" of restricted view passive infrared (PIR) motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite® Walkway System gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1cm/s (SD = 11.3cm/s), which improved to 1.1cm/s (SD = 9.1cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s our system had an average error of less than 7% without calibration and 1.1% with calibration.

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We report the discovery of a previously unknown massive Galactic star cluster at ℓ = 29.22 • , b = −0.20 • . Identified visually in mid-IR images from the Spitzer GLIMPSE survey, the cluster contains at least 8 late-type supergiants, based on followup near-IR spectroscopy, and an additional 3-6 candidate supergiant members having IR photometry consistent with a similar distance and reddening. The cluster lies at a local minimum in the 13 CO column density and 8 µm emission. We interpret this feature as a hole carved by the energetic winds of the evolving massive stars. The 13 CO hole seen in molecular maps at V LSR ∼ 95 km s −1 corresponds to near/far kinematic distances of 6.1/8.7±1 kpc. We calculate a mean spectrophotometric distance of 7.0 +3.7 −2.4 kpc, broadly consistent with the kinematic distances inferred. This location places it near the northern end of the Galactic bar. For the mean extinction of A V = 12.6 ± 0.5 mag (A K = 1.5 ± 0.1 mag), the color-magnitude diagram of probable cluster members is well fit by isochrones in the age range 18-24 Myr. The estimated cluster mass is ∼ 20, 000 M ⊙ . With the most massive original cluster stars likely deceased, no strong radio emission is detected in this vicinity. As such, this RSG cluster is representative of adolescent massive Galactic clusters that lie hidden behind many magnitudes of dust obscuration. This cluster joins two similar red supergiant clusters as residents of the volatile region where the end of our Galaxy's bar joins the base of the Scutum-Crux spiral arm, suggesting a recent episode of widespread massive star formation there.

We present the first resolved map of plane-of-sky magnetic field strength for a quiescent molecular cloud. GRSMC 45.60+0.30 subtends 40 × 10 pc at a distance of 1.88 kpc, masses 16,000 M ⊙ , and exhibits no star formation. Near-infrared background starlight polarizations were obtained for the Galactic Plane Infrared Polarization Survey using the 1.8m Perkins telescope and the Mimir instrument. The cloud area of 0.78 square degrees contains 2,684 significant starlight polarizations for 2MASS-matched stars brighter than 12.5 mag in H-band. Polarizations are generally aligned with the cloud's major axis, showing an average P.A. dispersion of 15 • ± 2 • and polarization of 1.8 ± 0.6%. The polarizations were combined with Galactic Ring Survey 13 CO spectroscopy and the Chandrasekhar-Fermi method to estimate plane-of-sky magnetic field strengths, with an angular resolution of 100 arcsec. The average plane-of-sky magnetic field strength across the cloud is 5.40 ± 0.04 µG. The magnetic field strength map exhibits seven enhancements, or 'magnetic cores.' These cores show an average magnetic field strength of 8.3 ± 0.9 µG, radius of 1.2 ± 0.2 pc, intercore spacing of 5.7 ± 0.9 pc, and exclusively subcritical mass-to-flux ratios, implying their magnetic fields continue to suppress star formation. The magnetic field strength shows a power law dependence on gas volume density, with slope 0.75 ± 0.02 for n H2 ≥ 10 cm −3 . This power law index is identical to those in studies at higher densities, but disagrees with predictions for the densities probed here.